Cooking quality, color, and texture profile analysis of a quinoa and lentil pasta (2024)

Quinoa (Chenopodium quinoa willd) and lentils (Lens culinaris) are ingredients used to enrich or substitute gluten in pasta manufacture due to their high nutritional content. The objective of this work was to develop quinoa noodles with lentils that have similar or superior attributes compared to the product with gluten. Therefore, we evaluated the cooking properties (cooking quality, hydration, rheology), color, and texture profile of noodles developed with different concentrations (10%, 20%, and 30%) of lentil flour (LF) in comparison to commercial wheat pasta (control). ANOVA comparisons were performed on cooking and texture profile attributes, with the best treatment being the one with values that did not significantly differ from the control sample (T0). Thus, T3 (70% quinoa grits and 30% LF) is the formulation that presents better and/or similar attributes to those of the control sample.

Index terms:
Quinoa: treatment; control sample

Quinoa (Chenopodium quinoa willd) e lentilhas (Lens culinaris) são ingredientes utilizados para enriquecer ou substituir o glúten em massas devido ao seu alto conteúdo nutricional. O objetivo deste trabalho foi desenvolver um macarrão de quinoa com lentilha com atributos semelhantes ou superiores ao produto com glúten. Para tanto, realizamos análise proximal e avaliamos as propriedades de cozimento (qualidade de cozimento, hidratação e reología), perfil de cor e textura de massas desenvolvidas com diferentes concentrações (10%, 20% e 30%) de farinha de lentilha (LF). Comparações de ANOVA foram realizadas nos atributos de cozimento e perfil de textura, sendo o melhor tratamento aquele com valores que não diferiram significativamente da amostra controle (T0). Assim, T3 é a formulação que apresenta atributos melhores e/ou semelhantes aos da amostra controle.

Termos para indexação:
Quinoa: tratamento; amostra controle

Global wheat production has increased steadily in recent years, but some factors could threaten its growth, such as climate change, pests, and diseases. Therefore, it is important to look for alternatives to replace wheat in the preparation of pasta. Some potential substitutes are quinoa and lentils, which are good sources of proteins, carbohydrates, fiber, and vitamins, have excellent functional and rheological properties, and are relatively inexpensive and accessible to consumers (FAO, 2011Food and Agriculture Organization of the United Nations - FAO. (2011). La Quinua: Cultivo milenario para contribuir a la seguridad alimentaria mundial. Informe técnico. Available in: Available in: https://www.fao.org/3/aq287s/aq287s.pdf Access in: February 22, 2024.
https://www.fao.org/3/aq287s/aq287s.pdf... ).

Quinoa flakes are made from quinoa grains through a pre-cooking and rolling process. Quinoa flakes and legume flours (e.g., lentil) are used as additional ingredients or partial replacements for wheat flour in the preparation of noodles, as their addition increases the protein content and also provides a unique flavor and texture (Burgos et al., 2019Burgos, V. E. et al. (2019). Physicochemical characterization and consumer response to new Andean ingredients-based fresh pasta: Gnocchi. International Journal of Gastronomy and Food Science, 16:100142. ). However, the gluten protein fraction in wheat flour (that provides a smooth surface and attractive and malleable appearance) makes it difficult to eliminate gluten from pasta dough without the use of gums and proteins. Not to mention that the characteristics and physical properties differ from gluten-containing products (Giménez et al., 2016Giménez, M. A. et al. (2016). Nutritional improvement of corn pasta-like product with broad bean (Vicia faba) and quinoa (Chenopodium quinoa). Food Chemistry, 199:150-156. ).

As most gluten-free products are generally made from refined flour of low nutrient content and considered inferior products, it is important to evaluate the physical and textural properties of the products used in pasta production (Giuberti et al., 2015Giuberti, G. et al. (2015). Cooking quality and starch digestibility of gluten free pasta using new bean flour. Food Chemistry , 175:43-49. ). This is imperative for developing new products with similar or better physical and nutritional properties than the original product.

Various studies have explored the potential of quinoa and legumes in the preparation of gluten-free pasta. Different levels of quinoa flour (up to 30%) led to increased protein and fiber contents but with a negative impact on texture and color (Demir & Bilgiçli, 2021Demir, B., & Bilgiçli, N. (2021). Utilization of quinoa flour (Chenopodium quinoa Willd.) in gluten-free pasta formulation: Effects on nutritional and sensory properties. Food Science and Technology International, 27(3):242-250. ). Pasta based on chickpea or lentil flour showed good cooking and texture properties, but a slight legume flavor (Bayomy & Alamri, 2022Bayomy, H., & Alamri, E. (2022). Technological and nutritional properties of instant noodles enriched with chickpea or lentil flour. Journal of King Saud University - Science, 34(3):101833. ). Extruded quinoa flour, potato starch, and tara gum negatively affected the firmness and cooking quality of the pasta which were overcome by increasing the concentration of lupine flour to 30% and using pea protein, especially without tara gum (Linares-García et al., 2019Linares-García, L. et al. (2019). Development of gluten-free and egg-free pasta based on quinoa (Chenopdium quinoa Willd) with addition of lupine flour, vegetable proteins and the oxidizing enzyme POx. European Food Research and Technology, 245(10):2147-2156. ).

The objective of this work was to develop quinoa noodles with lentils that have similar or superior attributes to the gluten product, without the need to add wheat flour, gums, or binding agents. The gluten-free noodles were compared with commercial wheat pasta (control sample) in terms of physical and nutritional properties. This work represents a step forward towards the development of healthier and more sustainable foods.

Raw material

Quinoa grits (QG) and lentil flour (LF) were acquired from the Naturkost company. The quinoa flakes belong to the Juli blanca variety from Cabana (Puno-Peru), the salt, the table water, and the noodles used as a control sample (T0) were purchased from a local market.

Pasta preparation

We prepared three formulations: Formulation T1: 90% QG -10% LF; formulation T2: 80% QG - 20% LF; and formulation T3: 70% QG - 30% LF. QG and LF (particle size 180-250 µm - AOAC 925.09) were mixed for 5 min. Subsequently, water (30%) with previously dissolved salt (4.8%) was added and kneaded for 10 min in a Nova Brand mixer (K50, Peru). Afterward, the dough was cold extruded and mixed again for another 10 min before the molding and cutting process. The dough obtained was subjected to a hot air dryer at 70°C for 4 h as recommended by Larrosa et al. (2016Larrosa, V. et al. (2016). Mathematical modeling of the drying process of gluten-free pasta according to temperature and relative humidity. INNOTEC, 11:54-58.).

Pasta hydration

Pasta products were hydrated following the method reported by Shang et al. (2023Shang, J. et al. (2023). Impact of A/B-type wheat starch granule ratio on rehydration behavior and cooking quality of noodles and the underlying mechanisms. Food Chemistry, 405:134896. ) and Ulloa et al. (2016Ulloa, J. A. et al. (2016). Mathematical modeling of hydration kinetics at different temperatures of four bean (Phaseolus vulgaris L) varieties produced in Mexico. CienciaUAT, 10(2):52-62.). Samples of 10 g of each formulation were immersed in 200 ml of distilled water at different temperatures (60 °C, 70 °C, and 80 °C). Every minute, portions of pasta were removed from the water, drained, blotted dry with an absorbent paper, weighed, and placed back into the beaker. This process was repeated until the maximum cooking time was reached. The moisture content was calculated for each time interval using a mass balance considering the initial mass of the samples, the initial humidity, and the mass obtained after each time interval.

Noodle hydration curves were generated by plotting water absorption (in g water/g dry solids) versus elapsed time (min). The hydration curves were evaluated for each temperature tested using the Peleg model (Corzo, Ramírez, & Bracho, 2008Corzo, O., Ramírez, O., & Bracho, N. (2008). Aplicación del modelo de peleg en el estudio de la transferencia de masa durante la deshidratación osmótica de laminas de mamey (Mammea americana L.). SABER. Revista Multidisciplinaria Del Consejo de Investigación de LaUniversidad de Oriente, 20(1):87-95.):

Where: M(t) moisture content (%) at time t (min); Mo Initial humidity (%); K₁ speed constant (min %^-1); capacity constant K₂ (%^-1)

Pasta cooking quality

Cooking tests were performed in triplicate for each formulation following the AACC 66-50 method (American Association of Cereal Chemists AACC, 2000American Association of Cereal Chemist - AACC. (2000). Approved methods of the american association of cereal chemists. American Association Cereal Chemistry, St. Paul, MN. 1200p.). Samples (25 g of dry pasta) were immersed in 300 ml of distilled water at 86 °C. The optimal cooking time (OCT) was measured when the white core in the noodles disappeared. Water absorption (WA) was determined by weight difference before and after cooking and reported as g of water/100 g. Finally, cooking losses (CL) were evaluated for 25 ml of cooking water subjected to 105 °C until constant weight in an oven (9140A, Kert Lab China). The result was expressed as g of solids/100 g of sample (López-Mejía, & Morales, 2020López-Mejía, N., & Morales Posada, N. B. (2020). Optimization of the formulation of gluten-free pasta enriched with dehydrated pumpkin pulp using the method of mix design. Brazilian Journal of Food Technology, 23:e2018299. ).

Color

The color of raw and cooked pasta was measured using a portable colorimeter (WR - 10QC, Fru, China) containing a CIE L*a*b* color space. The L* measurement corresponds to the luminosity (0-100), while a* represents the red-green coordinates and b* measures the yellow-blue coordinates. Six measurements were taken for each sample. Differences in L*, a*, and b* were compared to the total color difference (ΔE*) (Tiga et al., 2021Tiga, B. H. et al. (2021). Thermal and pasting properties of quinoa: Wheat flour blends and their effects on production of extruded instant noodles. Journal of Cereal Science , 97:103120. ).

Rheological properties

Measurements of rheological properties were carried out at 25 °C with a rheometer (MCR 72, Anton Paar Inc., Austria), using 5 g of cooked sample of each formulation. An amplitude scan was carried out to determine the linear viscoelastic region at a constant frequency of 10 rad/s and a strain of 0.1% (Sofi et al., 2020Sofi, S. A. et al. (2020). Quality characterization of gluten free noodles enriched with chickpea protein isolate. Food Bioscience, 36:100626.).

Texture profile analysis (TPA)

The texture of the cooked pasta was determined using a dynamometer (34tTM, Instron, USA) with a 5 kN load cell equipped with compression plates (P/75). The speed before the test was 0.50 mm/s and the deformation was 75% (Martinez et al., 2007Martinez, C. S. et al. (2007). Physical, sensory and chemical evaluation of cooked spaghetti. Journal of Texture Studies, 38(6):666-683. ).

Proximal analysis

The proximal analysis of the formulated pasta (T1, T2, and T3) and the control sample consisted of the quantification of moisture (NTP 206.011:2018Norma Técnica Peruana - NTP 206.011. (2018). Bizcochos, galletas y pastas o fideos. Determinación de humedad. Lima, Perú: Instituto Nacional de Calidad (INACAL).a), protein, fiber, fat (FAO), ash (NTP 206.012:2018Norma Técnica Peruana -NTP 206.012. (2018). Bizcochos y pastas o fideos. Determinación de cenizas. Lima, Perú: Instituto Nacional de Calidad (INACAL). b), and total carbohydrates that were determined by difference calculation from the results.

Design and statistical analysis

All determinations were performed in triplicate, except for the color test (n = 6), and the means and standard deviations were calculated. The results were analyzed by analysis of variance (ANOVA, p < 0.05) using the statistical program Statgraphics Centurion XVI (Statistical Graphics Corp., Herndon, VA).

Proximal analysis

Table 1 shows the nutritional composition of the formulations tested. Formulation T3 stood out for its high protein content (15.02%) and fat (1.67%) compared to the commercial sample (T0) and the other formulations in addition to having a lower amount of carbohydrates (73.25 %). Wójtowicz and Mościcki, (2014Wójtowicz, A., & Mościcki, L. (2014). Influence of legume type and addition level on quality characteristics, texture and microstructure of enriched precooked pasta. LWT - Food Science and Technology , 59(2P1):1175-1185. ) obtained similar protein values ​​by partially substituting lentil flour at 10% (12.23 g/100 g), 20% (13.79 g/100 g), 30% (14.87 g/100 g), and 40% (16.40 g/100 g). Gupta, Sharma and Reddy Surasani (2021Gupta, A., Sharma, S., & Reddy Surasani, V. K. (2021). Quinoa protein isolate supplemented pasta: Nutritional, physical, textural and morphological characterization. LWT - Food Science and Technology , 135:110045.) and Bouasla, Wójtowicz and Zidoune (2017Bouasla, A., Wójtowicz, A., & Zidoune, M. N. (2017). Gluten-free precooked rice pasta enriched with legumes flours: Physical properties, texture, sensory attributes and microstructure. LWT - Food Science and Technology, 75:569-577. ) also reported similar protein values. Bayomy and Alamri, (2022Bayomy, H., & Alamri, E. (2022). Technological and nutritional properties of instant noodles enriched with chickpea or lentil flour. Journal of King Saud University - Science, 34(3):101833. ) and Teterycz et al. (2020Teterycz, D. et al. (2020). Legume flour as a natural colouring component in pasta production. Journal of Food Science and Technology , 57(1):301-309. ) reached nutritional values ​​around 15.89 g/100 g (protein), 3.21 g/100 g (fat), and 4.58 g/100 g (fiber) in lentil and chickpea noodles. Noodles made with lentils and quinoa are an excellent source of protein because both legumes are high-quality ingredients in terms of protein intake. LF is recognized for containing a significant amount of proteins of plant origin and quinoa is one of the few plant species that contains essential amino acids (Torres, Lema González, & Galeano Loaiza, 2021bTorres Vargas, O. L., Lema González, M., & Galeano Loaiza, Y. V. (2021b). Optimization study of pasta extruded with quinoa flour (Chenopodium quinoa willd). CYTA - Journal of Food, 19(1):220-227. ). By combining both ingredients it is possible to increase the protein content in the final product, which is favorable for people who suffer from gluten intolerance or celiac disease.

Pasta hydration

The hydration curve of the noodles shows a gradual increase in water absorption over time and temperature (Figure 1). Pasta hydration occurred in all temperatures tested. Noodles began to absorb water and the absorption rates accelerated, reaching a maximum point where the amount of water stabilized (Adachi et al., 2021Adachi, S. et al. (2021). Water sorption kinetics of starch noodles with different cross-sectional shapes. Starch/Staerke, 73(5-6):2000235. ). Heat helps break down food structures and facilitates water to enter the noodles. High temperatures accelerate the decomposition process of starches to be easily digestible (Ogawa, & Adachi, 2016Ogawa, T., & Adachi, S. (2016). Moisture distribution and texture of spaghetti rehydrated under different conditions. Bioscience, Biotechnology and Biochemistry, 80(4):769-773. ) as observed at 70 °C and 80 °C with all treatments having greater water absorption in a short time.

Formulation T1 interacted with T0 (control) at 60 °C and 70 °C, whereas T3 only at 60 °C. Formulation T2 absorbed the least amount of water at the different temperatures.

Table 2 shows the effect of temperature on the hydration of quinoa and lentil pasta, as well as the values ​​and constants obtained through the Peleg model. The water absorption capacity (K₂) exhibited a high initial rate of 1.073 g water/g ds (T1 at 60 °C) and 1.031 g water/g ds (T0 at 80 °C).

K₂ constant increased at a higher temperature in formulations T0 (control) and T3, while decreasing in formulations T1 and T2. Formulation T0 has gluten and the protein network while formulation T3 has the highest amount of protein of all the treatments, which enables them to trap water. As temperature increases, proteins and fibers denature, facilitating water diffusion (Mastromatteo et al., 2012Mastromatteo, M. et al. (2012). Influence of heat treatment on the quality of functional gluten-free spaghetti. Food and Nutrition Sciences, 3(4):433-440. ).

Regarding the mass transfer rate, the higher the value of K₁, the greater the initial speed of water absorption. According to the value obtained from the Peleg model, formulation T2 had the highest water absorption rate in the initial stage at all three temperatures studied (16.28, 24.61, and 9.52 min g bs/g H₂O at 60 °C, 70 °C, and 80 °C, respectively). The Peleg model considers both the moisture content and the water absorption capacity of the food. Therefore, the specific combination of QG and LF in formulation T2 may be promoting a higher rate of water absorption compared to the other formulations.

Cunningham et al. (2007Cunningham, S. E. et al. (2007). Modelling water absorption of pasta during soaking. Journal of Food Engineering, 82(4):600-607. ) demonstrated in dried penne pasta (10 mm diameter) that the Peleg constants K₁ and K₂ decreased with temperature, and observed a porous and hom*ogeneous protein structure with few starch granules. Ogawa and Adachi (2017Ogawa, T., & Adachi, S. (2017). Drying and rehydration of pasta. In T. Ogawa & S. Adachi. Drying technology. Vol. 35, Issue 16, pp.1919-1949. ) obtained average estimated values ​​of K₁, K₂, and H_pred for wheat pasta in the range of 20 °C to 90 °C of 1.21 kg-H₂O/kg m.s, and 7.42 × 10^-4 1/s respectively. The equilibrium moisture content is limited by starch gelatinization while the initial rate of hydration is regulated by the diffusion of water through the pores of the dough. This can decrease cooked pasta quality and moisture content, which affects mechanical properties and optimal rehydration time (Ogawa, & Adachi, 2014Ogawa, T., & Adachi, S. (2014). Measurement of moisture profiles in pasta during rehydration based on image processing. Food and Bioprocess Technology, 7(5):1465-1471. ).

Cooking quality

Evaluating the cooking quality of the pasta involves considering the amount of solids released during cooking, the water absorption, and the swelling index (Torres et al., 2021aTorres, O. L., Lema, M., & Galeano, Y. V. (2021a). Effect of using quinoa flour (Chenopodium quinoa Willd.) on the physicochemical characteristics of an extruded pasta. International Journal of Food Science, Article ID 8813354. ). The OCT for T0 (commercial sample) was higher (8.4 min) compared to formulations T1 (5.35 min), T2 (6.22 min), and T3 (7.13 min) (Table 3). WA was lower in T2, whereas the values of IH were close to the control (T0). CL increased in T2 and T3.

The optimal cooking time and swelling index are lower in the formulations with QG and LF than in the control sample because flours without gluten generally cook faster than wheat flour (Table 3). Gluten is a protein that helps the dough expand and stay fluffy during cooking. In the absence of gluten, the dough does not have the same structure and tends to fall apart. For example, in the work of Romero and Zhang (2019Romero, H. M., & Zhang, Y. (2019). Physicochemical properties and rheological behavior of flours and starches from four bean varieties for gluten-free pasta formulation. Journal of Agriculture and Food Research, 1:100001.), noodles made with chickpea flour cooked in 5.5 min, while noodles made with wheat flour cooked in 10 min. In the work of Schoenlechner et al. (2010Schoenlechner, R. et al. (2010). Functional properties of gluten-free pasta produced from amaranth, quinoa and buckwheat. Plant Foods for Human Nutrition, 65(4):339-349. ) and Zhao et al. (2020Zhao, B. et al. (2020). Effects of gluten on rheological properties of dough and qualities of noodles with potato: Wheat flour blends. Cereal Chemistry, 97(3):601-611.), noodles made with quinoa and potato flour cooked in 3 and 4 min, while noodles made with wheat flour cooked in 9-10 min.

Feijoo et al. (2017Feijoo, J. C., Calderón, C. S., & Mora, E. M. (2017). Pruebas de cocción de pastas alimenticias elaboradas con harina de trigo - almidón de banano. Cumbres, 4:9-16. ) noted that the resistance to disintegration during cooking is directly affected by the complete substitution of wheat flour. In the case of gluten-free pasta, such as formulations T1, T2, and T3, starch polymers are less encapsulated, which can hinder the excessive swelling of starch granules and, therefore, the dispersion of components in the cooking water. CL are related to the disruption in the protein/starch matrix, which causes an uneven distribution of water inside the noodles.

Rheological properties

In the rheological testing of dough, the storage modulus (G’) is used to measure the strength of the pasta, while the loss modulus (G’’) is used to measure its elasticity (Motta Romero et al., 2017Motta Romero, H. et al. (2017). Dough rheological properties and texture of gluten-free pasta based on proso millet flour. Journal of Cereal Science, 74:238-243. ). The strength and elasticity of pasta are its ability to resist deformation and to return to its original shape after being deformed, respectively. Figure 2 shows that the storage modulus (G’) is greater than the loss modulus (G’’) (Figure 3), which indicates that all kinds of pasta are resistant to deformation and have a more elastic than viscous behavior with good bonding characteristics and dense internal structure (Sofi et al., 2020Sofi, S. A. et al. (2020). Quality characterization of gluten free noodles enriched with chickpea protein isolate. Food Bioscience, 36:100626.). Pastas with high moisture and protein content have a higher G’ value. This behavior is commonly observed in elastic solids. Torres Vargas et al. (2021bTorres Vargas, O. L., Lema González, M., & Galeano Loaiza, Y. V. (2021b). Optimization study of pasta extruded with quinoa flour (Chenopodium quinoa willd). CYTA - Journal of Food, 19(1):220-227. ) and Zhang et al. (2018Zhang, D., Mu, T., & Sun, H. (2018). Effects of starch from five different botanical sources on the rheological and structural properties of starch-gluten model doughs. Food Research International, 103:156-162. ) obtained similar results with doughs based on quinoa and other plant species (starch-gluten), respectively. A high storage modulus suggests an intense interaction between particles or a stable network-like structure (Burgos et al., 2019Burgos, V. E. et al. (2019). Physicochemical characterization and consumer response to new Andean ingredients-based fresh pasta: Gnocchi. International Journal of Gastronomy and Food Science, 16:100142. ).

Texture profile

Only hardness (increased in T1 and T2) and fracture ability (increased in T2 and T3) differed in some formulations compared to the control, whereas the other parameters (cohesiveness, elasticity, chewiness, and gumminess) were unchanged (Table 4).

The hardness and chewiness of cooked pasta are determined by the presence of proteins linked to gliadins, while factors preventing the disintegration of pasta when cooked are glutenins and the low proportion of water-soluble proteins.

Bouasla, Wójtowicz and Zidoune (2017Bouasla, A., Wójtowicz, A., & Zidoune, M. N. (2017). Gluten-free precooked rice pasta enriched with legumes flours: Physical properties, texture, sensory attributes and microstructure. LWT - Food Science and Technology, 75:569-577. ) report the hardness of hydrated pasta to be 0.44 N for rice pasta and 0.21 - 0.40 N for pasta enriched with legume flours. The same trends were observed by Wójtowicz and Mościcki (2014)Wójtowicz, A., & Mościcki, L. (2014). Influence of legume type and addition level on quality characteristics, texture and microstructure of enriched precooked pasta. LWT - Food Science and Technology , 59(2P1):1175-1185. for pre-cooked soft wheat pasta enriched with legume flours. The fiber fractions of legume flour can cause the formation of cracks or discontinuities within the pasta strand that weaken the pasta structure.

Color

The elements that define the color of pasta are the ingredients that contain carotenoids, pigments that contribute to the yellow color, as well as the duration and temperature of the cooking process that can alter the Maillard reaction. Gluten-free flours tend to produce darker or paler pasta (Mastromatteo et al., 2012Mastromatteo, M. et al. (2012). Influence of heat treatment on the quality of functional gluten-free spaghetti. Food and Nutrition Sciences, 3(4):433-440. ). Quinoa pasta with lentils naturally does not contain wheat flour or eggs, foods that contribute to the color, nor do they have the characteristic color of commercial pasta. According to the color variation (ΔE), the color difference is perceptible to the naked eye compared to the control sample (T0).

When examining the CIEL*a*b* coordinates obtained for the various formulations (Table 5 and Figure 4), the decrease in the values of L*, a*, and b* in the raw pasta is evident, in addition to the notable difference in values compared to T0. As the addition of LF increased, the values decreased in both raw and cooked pasta.

Petitot et al. (2010Petitot, M. et al. (2010). Fortification of pasta with split pea and faba bean flours: Pasta processing and quality evaluation. Food Research International, 43(2):634-641. ) obtained similar values ​​of pasta color attributes. In pasta with peas and beans, a* values ​​ranged between 5.0-21.5 and b* values ​ between 7.8-20.3, data similar to ours (Marengo et al., 2018Marengo, M. et al. (2018). Enriching gluten-free rice pasta with soybean and sweet potato flours. Journal of Food Science and Technology, 55(7):2641-2648. ); Regarding luminosity values ​​(L*), López-Mejía & Morales, (2020López-Mejía, N., & Morales Posada, N. B. (2020). Optimization of the formulation of gluten-free pasta enriched with dehydrated pumpkin pulp using the method of mix design. Brazilian Journal of Food Technology, 23:e2018299. ) obtained ranges from 64.02-67.85 in pasta enriched with pumpkin. Each value obtained in the present work is between that obtained by the aforementioned authors. It should be noted that as long as foods with a high content of carotenoids or dyes are used, the pasta will have a pale color. Our formulations with quinoa and lentils do not contain this component in abundance, which is why the color obtained is pale yellow (Figure 4).

In this study, significant differences in variables between the developed formulations (T1,T2, and T3) and the control sample (T0) were evident. While all formulations adapted better to hydration temperatures than the control, T0 performed better in rheology tests. T3, despite having high protein (15%), showed the most similar cooking quality to T0. Color and texture analyses revealed significant differences from the control. Overall, T3 appears to offer the best balance of properties similar to the control.

The authors thank Nelida Mayta, a member of Naturkost Perú SAC, for her support in the experiments.

Editor: Renato Paiva